A transportation network for vehicles can include several interconnected main routes on which separate vehicles travel between locations. For example, a transportation network may be formed from interconnected railroad tracks with rail vehicles traveling along the tracks. The vehicles may travel according to schedules that dictate where and when the vehicles are to travel in the transportation network. The schedules may be coordinated with each other in order to arrange for certain vehicles to arrive at various locations in the transportation network at desired times and/or in a desired order. Each vehicle traveling through the network may also be controlled according to a pre-set plan for accomplishing a mission being performed by the vehicle.
Fuel is a large expense for a railroad. Continued improvement in fuel efficiency is important to minimizing operating costs as well as to reducing emissions for regulatory purposes. New technologies or initiatives may be developed to reduce fuel consumption. One problem encountered with new technologies or initiatives that seek to reduce fuel consumption and/or emission generation is that it can be difficult to evaluate or quantify the effectiveness of such initiatives due to difficulties in measuring fuel consumed by a vehicle or vehicles using the new technology or initiative.
In certain current attempts to evaluate fuel savings, each locomotive of a train separately transmits information to an off-board recipient regarding the operation of that particular locomotive for off-board processing. Such off-board processing is done retrospectively after the data has been transmitted and stored, and can involve human entry and/or computation of fuel consumption. The reporting process alone may take days as locomotives come into range and report. In addition to the time consumed and errors caused by such entry, additional errors due to improper correlation of data also reduce the quality of current fuel consumption computations. For example, to understand how much fuel is used between two given points, data sent from a locomotive may be combined with data from an automatic equipment identification (AEI) reader, with information from the two devices correlated by a time stamp. However, a time stamp from a locomotive from which data is sent may not correlate with a time stamp from the AEI reader, thus resulting in an error in the location or route being evaluated.
Also, if one locomotive encounters a communication problem, then the data for the entire train may be incomplete and thereby compromised. Further, because of the number of sources and potential for error in current systems, large sets of data are required to have an acceptable level of confidence in the results. However, it may take a considerable amount of time to accumulate enough data to have reliable results. Thus, it may take, for example, several months before it is known if a given technology or technique is effective in reducing fuel consumption, or how much fuel is saved by a given technique or techniques.
Thus, current systems have a large amount of inaccuracy as well as an undesirable time lag before results are known with an acceptable level of confidence. These problems may compound each other, as the inaccuracy requires more trips to be taken to have any level of confidence, with the required additional trips resulting in an even greater time lag.
A need exists for improved analysis of fuel consumption.